Measuring diagnoses: ICD code accuracy.

Objective. To examine potential sources of errors at each step of the described inpatient International Classification of Diseases (ICD) coding process. Data Sources/Study Setting. The use of disease codes from the ICD has expanded from classifying morbidity and mortality information for statistical...

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Publicado en:Health Services Research Vol. 40; no. 5P2; pp. 1620 - 1640
Autores principales: O'Malley KJ, Cook KF, Price MD, Wildes KR, Hurdle JF, Ashton CM
Formato: tables/charts Journal Article
Publicado: Wiley-Blackwell Oct2005
Acceso en línea:Ver este registro en EBSCOhost
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      dt: Oct2005
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      pub: Wiley-Blackwell
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        10.1111/j.1475-6773.2005.00444.x
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        atl: Measuring diagnoses: ICD code accuracy.
      aug:
        au:
          O'Malley KJ
          Cook KF
          Price MD
          Wildes KR
          Hurdle JF
          Ashton CM
        affil: Pearson Educational Measurement, 2201 Donley Drive, Suite 195, Austin, TX 78758
      sug:
        subj:
          Data Collection Methods
          Health Services Research Methods
          International Classification of Diseases
          Coding
          Diagnostic Errors
          Disease Classification
          Reproducibility of Results
      ab: Objective. To examine potential sources of errors at each step of the described inpatient International Classification of Diseases (ICD) coding process. Data Sources/Study Setting. The use of disease codes from the ICD has expanded from classifying morbidity and mortality information for statistical purposes to diverse sets of applications in research, health care policy, and health care finance. By describing a brief history of ICD coding, detailing the process for assigning codes, identifying where errors can be introduced into the process, and reviewing methods for examining code accuracy, we help code users more systematically evaluate code accuracy for their particular applications. Study Design/Methods. We summarize the inpatient ICD diagnostic coding process from patient admission to diagnostic code assignment. We examine potential sources of errors at each step and offer code users a tool for systematically evaluating code accuracy. Principle Findings. Main error sources along the âpatient trajectoryâ include amount and quality of information at admission, communication among patients and providers, the clinician's knowledge and experience with the illness, and the clinician's attention to detail. Main error sources along the âpaper trailâ include variance in the electronic and written records, coder training and experience, facility quality-control efforts, and unintentional and intentional coder errors, such as misspecification, unbundling, and upcoding. Conclusions. By clearly specifying the code assignment process and heightening their awareness of potential error sources, code users can better evaluate the applicability and limitations of codes for their particular situations. ICD codes can then be used in the most appropriate ways.
      pubtype: Academic Journal
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        tables/charts
        Journal Article
      ougenre: Article
    language: English
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